• Journal of the Korea Academia-Industrial cooperation Society
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• v.15 no.2
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• pp.1126-1139
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• 2014

World is experiencing abnormal weather caused by urbanization and industrialization increasing greenhouse gas and one of these phenomenon domestically happening is flood and drought. The increase of green-house gases is due to urbanization and industrialization acceleration which are causing abnormal climate changes such as the El Nino and a La Nina phenomenon. It is expected that there will be many difficulties in water management, especially considering the topography and seasonal circumstances in Korea. Unlike in the past, a variety of water conservation initiatives have been undertaken like the river-management flow and water capacity expansion projects. To meet the increasing demand for water resources, new environmentally-friendly small and medium-sized dams have been built. Therefore, the development of a new paradigm for water resources management is essential. This study shows that additional security is needed for potential water resources through diversion tunnels and is very important to consider for future water supplies and situations. Using RCP 6.0 and RCP 8.5 in representative concentration pathway climate change scenario, specific hydrologic data of study basin was produced to analyze past observed basin rainfall tendency which showed both scenario 5%~9% range increase in rainfall. Through sensitivity analysis using objective function, population in highest goodness was 1000 and cross rate was 80%. In conclusion, it is expected that the results from this study will help to make long-term and stable water supply plans by using the potential water resource evaluation model which was applied in this study.

• Korean Journal of Remote Sensing
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• v.38 no.6_2
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• pp.1709-1722
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• 2022

The rise in temperature induced by global warming caused in El Nino and La Nina, and abnormally changed the temperature of seawater. Rainfall concentrates in some locations due to abnormal variations in seawater temperature, causing frequent abnormal floods. It is important to rapidly detect flooded regions to recover and prevent human and property damage caused by floods. This is possible with synthetic aperture radar. This study aims to generate a model that directly derives flood-damaged areas by using modified U-NET and TerraSAR-X images based on Multi Kernel to reduce the effect of speckle noise through various characteristic map extraction and using two images before and after flooding as input data. To that purpose, two synthetic aperture radar (SAR) images were preprocessed to generate the model's input data, which was then applied to the modified U-NET structure to train the flood detection deep learning model. Through this method, the flood area could be detected at a high level with an average F1 score value of 0.966. This result is expected to contribute to the rapid recovery of flood-stricken areas and the derivation of flood-prevention measures.

• Proceedings of the KSRS Conference
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• 2006.03a
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• pp.101-104
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• 2006

In the Korean seas, Sea Surface Temperature (SST) and Thermal Fronts (TF) were analyzed temporally and spatially during 8 years from 1993 to 2000 using NOAA/AVHRR MCSST. As the result of EOF method applying SST, the variance of the 1st mode was 97.6%. It is suitable to explain SST conditions in the whole Korean seas. Time coefficients were shown annual variations and spatial distributions were shown the closer to the continent the higher SST variations like as annual amplitudes. The 2nd mode presented higher time coefficients of 1993, 94, and 95 than those of other years. Although the influence is a little, that can explain ElNINO effect to the Korean seas. TF were detected by Sobel Edge Detection Method using gradient of SST. Consequently, TF were divided into 4 fronts; the Subpola. Front (SPF) dividing into the north and south part of the East sea, the Kuroshio Front (KF) in the East China Sea (ESC), the South Sea Coastal Front (SSCF) in the South sea, and the Tidal Front in the West sea. TF located in steep slope of submarine topography. The distributions of 1st mode in SST were bounded in the same place, and these results should be considered to influence of seasonal variations. To discover temporal and spatial variations of TF,SST gradient values were analyzed by EOF. The time coefficients fo the 1st mode (variance : 64.55%) showed distinctive annual variations and SPF, KF, and SSCF was significantly appeared in March. the spatial distributions of the 2nd mode showed contrast distribution, as SPF and SSCF had strong '-' value, where KF had strong '+' value. The time of '+' and '-' value was May and October, respectively. Time coefficients of the 3rd mode had 2 peaks per year and showed definite seasonal variations. SPF represented striking '+' value which time was March and October That was result reflected time of the 1st and 2nd mode. We can suggest specific temporal and spatial variations of TF using EOF.